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This study attempts to use a new source of data collection from open government data sets to identify potential academic social networks (ASNs) and defines their collaboration patterns. The purpose of this paper is to propose a direction that may advance our current understanding on how or why ASNs are formed or motivated and influence their research collaboration.

This study first reviews the open data sets in Taiwan, which is ranked as the first state in Global Open Data Index published by Open Knowledge Foundation to select the data sets that expose the government’s R&D activities. Then, based on the theory review of research collaboration, potential ASNs in those data sets are identified and are further generalized as various collaboration patterns. A research collaboration framework is used to present these patterns.

Project-based social networks, learning-based social networks and institution-based social networks are identified and linked to various collaboration patterns. Their collaboration mechanisms, e.g., team composition, motivation, relationship, measurement, and benefit-cost, are also discussed and compared.

In traditional, ASNs have usually been known as co-authorship networks or co-inventorship networks due to the limitation of data collection. This study first identifies some ASNs that may be formed before co-authorship networks or co-inventorship networks are formally built-up, and may influence the outcomes of research collaborations. These information allow researchers to deeply dive into the structure of ASNs and resolve collaboration mechanisms.

This paper aims to introduce a systematic computing and analytical procedure that is applied to the co-author network to identify the temporal evolution and growth of research collaborations in the area of e-governance. The empirical analysis of the temporal co-author network can trace the emerging authors and knowledge bursts over time.

The study applied social network theory to trace the author collaboration patterns in the domain of e-governance. Analysis of the co-author network using micro and macro parameters was done to trace the temporal evolution of the author collaborations.

E-governance is a multi-disciplinary research domain split over streams of management, politics, information technology and electronics. Hence, research collaborations play a significant role in its advancement. The knowledge sharing between individual authors, institutions and groups through research collaborations, resulting in extensive sharing of data, equipment and research methods, has boosted research activities and development in e-governance. In this paper, the authors systematically analyse the current scenario of research collaborations in the area of e-governance using co-author network to estimate its impact on the advancement of the field. The authors also analysed the temporal evolution of the co-author networks, which show remarkable growth of research collaborations in the domain of e-governance from the year 2000.

The co-author network analysis is only a proxy measure for the analysis of research collaborations. The names of the authors and the university affiliations used in the article are as retrieved from the research repository of Scopus. The degree, citations and other parameters related with authors have scope only within the environment of the co-author network used in the analysis. The criteria used in the study is limited to the degree of research collaborations and the number of co-authored publications in the giant component of the co-author network.

Institutions, authors and governments can trace and select suitable topics and choose research groups of co-authors over the world for future research collaborations in e-governance. The knowledge about the emerging and most discussed topics gives an overview of the global research trends of e-governance.

The study identified the evolution of creative collaborations in e-governance in the global perspective. The methodology introduced here is helpful to detect the proficient and productive author collaborations and the spectrum of related e-governance research topics associated with them. As the author collaborations can be mapped to the institutional and country-level collaborations, the information is helpful for researchers, institutions and governments to establish the best collaborations in e-governance research based on the author proficiency, collaboration patterns and research topics as per the requirements.

The paper introduces a novel research methodology using temporal analysis of co-author network to identify the evolution of research patterns and the associated research topics.

This study applies D3.js and social network analysis (SNA) to examine the impact of collaboration patterns, research productivity patterns and publication patterns on the Ministry of Education (MOE) evaluation policies across all Management Information Systems (MIS) departments in Taiwan.

This study first retrieved data from the Ministry of Science and Technology of Taiwan (MOST) website from 1982 to 2015, the Journal Citation Reports (JCR) website, the Web of Science (WOS) website and Google Scholar. Then it applied power-law degree distribution, cumulative distribution function, weighted contribution score, exponential weighted moving average and network centrality score to visualize the MIS collaborations and research patterns.

The analysis concluded that most MIS professors focused primarily on SCIE-/SSCI-/TSSCI-/core indexed journals after 2005. Professors from public universities were drawn to collaboration and publishing in high-quality-based journals, while professors from private universities focused more on quantity-based publications. Female professors, by contrast, have a slightly higher single-authorship publication rate in SCIE-/SSCI-/TSSCI-indexed journals than do male professors. Meanwhile, professors in northern Taiwan emphasized quantity-based journal publications, while a focus on quality was more typical in the south. Furthermore, National Cheng Kung University has the most single-authorship or intrauniversity publications in SCIE-/SSCI-/TSSCI-/core journals, and National Sun Yat-Sen University published more SSCI-indexed articles than SCIE-indexed articles. All of these findings show that there is an explicit relation between MOE evaluation policies and MIS faculty members' collaboration/publication strategies.

The above findings explain how MOE evaluation policies affected MIS faculty members' collaboration and publication strategies in Taiwan, and the authors hope that such findings can constitute a resource for understanding and characterizing networking with MIS departments in Taiwan.

The purpose of this paper is to apply social network analysis (SNA) to study faculty research productivity, to identify key leaders, to study publication keywords and research areas and to visualize international collaboration patterns and analyze collaboration research fields from all Management Information System (MIS) departments in Taiwan from 1982 to 2015.

The authors first retrieved results encompassing about 1,766 MIS professors and their publication records between 1982 and 2015 from the Ministry of Science and Technology of Taiwan (MOST) website. Next, the authors merged these publication records with the records obtained from the Web of Science, Google Scholar, IEEE Xplore, ScienceDirect, Airiti Library and Springer Link databases. The authors further applied six network centrality equations, leadership index, exponential weighted moving average (EWMA), contribution value and k-means clustering algorithms to analyze the collaboration patterns, research productivity and publication patterns. Finally, the authors applied D3.js to visualize the faculty members' international collaborations from all MIS departments in Taiwan.

The authors have first identified important scholars or leaders in the network. The authors also see that most MIS scholars in Taiwan tend to publish their papers in the journals such as Decision Support Systems and Information and Management. The authors have further figured out the significant scholars who have actively collaborated with academics in other countries. Furthermore, the authors have recognized the universities that have frequent collaboration with other international universities. The United States, China, Canada and the United Kingdom are the countries that have the highest numbers of collaborations with Taiwanese academics. Lastly, the keywords model, system and algorithm were the most common terms used in recent years.

This study applied SNA to visualize international research collaboration patterns and has revealed some salient characteristics of international cooperation trends and patterns, leadership networks and influences and research productivity for faculty in Information Management departments in Taiwan from 1982 to 2015. In addition, the authors have discovered the most common keywords used in recent years.

By exploring the patterns of co-authorship, this paper aims to identify the degree and type of research collaboration in Malaysia.

A total of 22,244 publication records from five research universities in Malaysia were retrieved from Scopus database. Journal articles published for the period between 2008 and October 2011 were collected. Indicators such as number of authors, subject areas, number of local institutions and foreign countries, were analysed using simple statistical tools to identity the degree and type of collaboration.

The findings reveal that in Malaysia, researchers tend to work in teams but collaboration is more dominant in science-based research than social sciences. Academics published extensively with their colleagues from the same university or from other academic institutions, but there is little collaboration with researchers from public research institutes or industry. In terms of international collaboration, Iran, India, UK, Japan and the USA are the top five collaborating countries. Disciplines with significant international collaboration are physics and astronomy; chemistry; agricultural and biological sciences; engineering; health profession and computer sciences.

This paper is among the few that study the patterns of co-authorship in Malaysia and most probably the first to examine the patterns in the Malaysian research universities. The study highlights the skewed distribution of co-authorship patterns where there is limited evidence of cross sectors collaboration in journal publication. The findings call for policy makers as well as universities to look into the constraints as well as drivers that would enhance the linkage of different actors in the national research system.

National collaboration is an important topic for the development of digital humanities (DH). However, the collaboration patterns of DH have not been well studied in terms of development stages and collaboration characteristics. This paper aims to reveal the typical patterns of country-level collaboration in the global environment of DH based on research capacity, network features and influence indicators.

We systematically designed a pipeline procedure based on the methods of bibliometrics and altmetrics to analyze global DH-related publications from two popular databases. The process includes the division of development stages, the identification of typical characteristics, the analysis of collaboration networks and the correlation test for different influences across countries.

The findings show that the collaboration in DH has certain characteristics and evolutionary patterns – with 2007 as the turning point that presents a gradual alteration from the strong competition of nation giants and the dominance of domestic collaboration to diversified international cooperation within regional alliances and a clear positive effect on national influence (both academic and social levels) by international collaboration. Some relevant suggestions are also put forward.

The study demonstrates not only the evidence of distinct patterns of country-level collaboration for DH during its evolutionary period as well as collaboration types and structures but also the positive effect of international collaboration on the enhancement of both academic influence and social attention. Moreover, the proposed analytical procedure provides insightful ideas around DH development from both the bibliometric and altmetric views, which can be an extensible framework for other scholarly collaboration research.

This study aims to analyze the distribution of novelty among scholarly papers in the field of library and information science (LIS) in China. Specifically, this study explores the distribution of novelty of papers in various journals, research topics and different periods. It is possible to understand the characteristics of LIS research in China and what factors have influenced it.

This paper collects articles published in Chinese library science journals indexed by the Chinese Social Sciences Citation Index from 2000 to 2022. The BERTopic model is used based on abstracts of the papers and to obtain the topic of each paper. Based on the combination innovation theory of reference pairs cited by focal papers, novelty scores of all papers are calculated. Next, this paper analyzes the novelty of papers under different topics. Finally, this paper analyzes the differences in author collaboration patterns across various topics, aiming to explain how these differences relate to the novelty of papers from a collaborative perspective.

This study shows that archival research topics have lower novelty than papers on journal evaluation and patent technology in Chinese LIS. Research papers in this field are gradually becoming more novel over time. Papers on different topics and with varying degrees of novelty exhibit distinct author collaboration patterns, with low-novelty topics more frequently featuring solo authorship, while high-novelty topics tend to involve a higher percentage of inter-institutional collaboration.

This study investigates the novelty characteristics of research papers on different topics in the field of LIS in China. The authors’ contribution includes visualizing research hotspots and trends in the field and analyzing authors’ collaboration patterns at the level of research topics, thereby providing new perspectives on the factors affecting the novelty of these papers.

During recent decades, research institutions have increased collaboration with other institutions since it is recognized as a good practice that improves their performance. However, they do not usually consider external collaborations as a strategic issue despite their benefits. The purpose of this paper consists of identifying different patterns of collaboration and internationalization of universities, with the aim of helping managers and policy makers to take decisions related to their national research policies.

Co‐authorship analysis has been used in conjunction with social network analysis to model inter‐institutional collaborations as networks, extracting these collaborations from the Web of Science database. Using several structural properties of the extracted networks and applying a statistical treatment, the main profiles of collaborations and internationalization have been obtained.

Obtained results distinguish three patterns of collaborations according to the intensity and scope of collaborations. The statistical treatment also provides a segmentation of universities according to their collaboration profiles. Finally, universities are represented in bi‐dimensional maps using external collaborations as a measure of similarity.

Although this study is restricted to English universities, it could probably be extended at least to other countries in the European Union or even other developed countries.

Research and institutions productivity are usually linked to the amount of received funding. The use of indicators related to internationalization of institutions can help to avoid a bias in favour of research quantity rather than quality, and towards a short‐term performance rather than a long‐term research capacity.

As a difference to previous works, this paper analyses networks of collaboration from the viewpoint of institutions. More specifically, the combination of social network analysis and factor analysis is used to identify patterns of collaboration among institutions. A longitudinal study is also included to demonstrate that the obtained categorization of universities is maintained over time.

The purpose of this paper is to examine the structure, patterns and themes of cross-national collaborations in Digital Humanities research through the application of social network analysis and visualization tools.

The sample includes articles containing Digital Humanities research in the Web of Science Core Collection as of December 2018. First, co-occurrence data representing collaborations among nations were extracted from author affiliations. Second, the descriptive statistics, network indicators and international communities were calculated. Third, the research topics of different cross-national collaboration communities based on ISI keywords, author keywords, title and abstracts were detected.

The results show that the scope of international collaborations in Digital Humanities research is broad, but the distribution among nations is unbalanced. The USA, Germany and England were identified as the major contributors. Five research communities are identified, led by the USA, Germany, England, Belgium and France. The communities share common research topics such as history, GIS, text mining, visualization, while each has its own research emphasis.

This study applied various informetric methods and tools to reveal the collaboration structure, patterns and themes among nations in Digital Humanities research.

The ranking of universities and other research-intensive institutions in global ranking systems is based on numerous indicators, including number of articles with external collaboration, number of articles with international collaboration, number of articles with industry collaboration as well as co-patents with industry. The purpose of this paper is to examine university–industry research collaboration in Ghana, with the aim of exploring the relationship between the research output collaborations in the top four universities in Ghana and industry across different geographical scales.

This study’s data was obtained from the SciVal database, which drawn its data from the Scopus bibliographic and citation database. The bibliographic and citation data were extracted using a search of the publications affiliated to the University of Ghana, for the period 2011–2020.

Key findings demonstrate a constant rise in the number of research publications by the selected universities over time. Research collaboration intensity in the selected universities in terms of co-authored publications was higher as compared to single-authored publications. University–industry research co-authorships were, however, lower when compared to university–university research co-authorships. The university–industry research co-authorships occurred mostly with Europe, Asia-Pacific and North American-based institutions as opposed to African-based institutions. In Ghana, four industry-based institutions were engaged in intensive research with the selected universities.

This study demonstrates that, for each selected university, it is possible to measure the performance of individual universities in both intra-regional and international collaboration. Such results may be useful in informing policy as well as merit-based public funding of universities in Ghana.